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Dennis OConnor

Apple and Google have a clever way of encouraging people to install contact-tracing app... - 0 views

www.theverge.com/...s-pros-cons-quarantine-testing

data tracking covid

shared by Dennis OConnor on 14 Apr 20 - No Cached
  • Apple and Google surprised us with an announcement that the companies are spinning up a system to enable widespread contact tracing in an effort to contain the COVID-19 pandemic.
  • The basic idea is that as jurisdictions flatten the curve of infection and begin to consider re-opening parts of society, they need to implement a comprehensive “test and trace” scheme.
  • First, the companies said that by phase two of their effort, when contact tracing is enabled at the level of the operating system, they will notify people who have opted in to their potential exposure to COVID-19 even if they have not downloaded the relevant app from their public health authority.
  • ...4 more annotations...
  • Apple and Google said they recognized the importance of not allowing people to trigger alerts based on unverified claims of a COVID-19 infection. Instead, they said, people who are diagnosed will be given a one-time code by the public health agency, which the newly diagnosed will have to enter to trigger the alert.
  • Google said it would distribute the operating system update through Google Play services, a part of Android controlled by the company that allows it to reach the majority of active devices.
  • Singapore saw only 12 percent adoption of its national contact-tracing app. Putting notifications at the system level represents a major step forward for this effort, even if still requires people to opt in.
  • the companies promised to use the system only for contact tracing, and to dismantle the network when it becomes appropriate.
Dennis OConnor

The Challenge of Tracking COVID-19's Stealthy Spread - NIH Director's Blog - 0 views

directorsblog.nih.gov/...king-covid-19s-stealthy-spread

covid contact-tracking research

shared by Dennis OConnor on 01 May 20 - No Cached
  • The first thing that testing may help us do is to identify those SARS-CoV-2-infected individuals who have no symptoms, but who are still capable of transmitting the virus.
  • The second way we can use testing is to identify individuals who’ve already been infected with SARS-CoV-2, but who didn’t get seriously ill and can no longer transmit the virus to others.
Dennis OConnor

Which Covid-19 Data Can You Trust? - 0 views

hbr.org/...ch-covid-19-data-can-you-trust

data visualization data covid Trustworthy

shared by Dennis OConnor on 10 May 20 - No Cached
  • incomplete or incorrect data can also muddy the waters, obscuring important nuances within communities, ignoring important factors such as socioeconomic realities, and creating false senses of panic or safety, not to mention other harms such as needlessly exposing private information.
  • Right now, bad data could produce serious missteps with consequences for millions.
  • Whether you’re a CEO, a consultant, a policymaker, or just someone who is trying to make sense of what’s going on, it’s essential to be able to sort the good data from the misleading — or even misguided.
  • ...24 more annotations...
  • These non-transparent, un-validated interventions — which are now being rolled out (or rolled back) in countries such as China, India, Israel and Vietnam — are in direct contravention to the open cross-border collaboration that scientists have adopted to address the Covid-19 pandemic.
  • Data products that are too broad, too specific, or lack context.
  • Public health practitioners and data privacy experts rely on proportionality
  • only use the data that you absolutely need for the intended purpose and no more.
  • Even data at an appropriate spatial resolution must be interpreted with caution — context is key.
  • Simply presenting them, or interpreting them without a proper contextual understanding, could inadvertently lead to imposing or relaxing restrictions on lives and livelihoods, based on incomplete information.
  • The technologies behind the data are unvetted or have limited utility.
  • Both producers and consumers of outputs from these apps must understand where these can fall short.
  • In the absence of a tightly coupled testing and treatment plan, however, these apps risk either providing false reassurance to communities where infectious but asymptomatic individuals can continue to spread disease, or requiring an unreasonably large number of people to quarantine.
  • Some contact-tracing apps follow black-box algorithms, which preclude the global community of scientists from refining them or adopting them elsewhere.
  • common red flags
  • Models are produced and presented without appropriate expertise.
  • Epidemiological models that can help predict the burden and pattern of spread of Covid-19 rely on a number of parameters that are, as yet, wildly uncertain.
  • n the absence of reliable virological testing data, we cannot fit models accurately, or know confidently what the future of this epidemic will look like
  • and yet numbers are being presented to governments and the public with the appearance of certainty
  • Read Carefully and Trust Cautiously
  • Transparency: Look for how the data, technology, or recommendations are presented.
  • Thoughtfulness: Look for signs of hubris.
  • Example: Telenor
  • Expertise: Look for the professionals. Examine the credentials of those providing and processing the data.
  • Open Platforms: Look for the collaborators.
  • technology companies like Camber Systems, Cubeiq and Facebook have allowed scientists to examine their data,
  • The Covid-19 Mobility Data Network, of which we are part, comprises a voluntary collaboration of epidemiologists from around the world analyzes aggregated data from technology companies to provide daily insights to city and state officials from California to Dhaka, Bangladesh
  • This pandemic has been studied more intensely in a shorter amount of time than any other human event.
  • Dennis OConnor on 10 May 20
     
    "This pandemic has been studied more intensely in a shorter amount of time than any other human event. Our globalized world has rapidly generated and shared a vast amount of information about it. It is inevitable that there will be bad as well as good data in that mix. These massive, decentralized, and crowd-sourced data can reliably be converted to life-saving knowledge if tempered by expertise, transparency, rigor, and collaboration. When making your own decisions, read closely, trust carefully, and when in doubt, look to the experts."
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